Summary of Key Points
This article uses the example of a “bad movie” that experiences a surge in box office thanks to online discussions to highlight the core contradiction of the AI era: while there is an abundance of information and stories, human attention, being limited to 24 hours a day, has become a new scarce resource. This scarcity of attention profoundly affects the pricing logic in financial markets, determining which stories can influence prices, the intensity of price fluctuations, the gap between expectations and reality, and the varying speeds at which different assets are priced.
Detailed Analysis
1. AI Increases the Number of Stories, but Our Attention is Limited
AI has reduced the cost of creating narratives. The same technological breakthrough (such as an AI chip) can be interpreted in various ways, such as “increased productivity,” “surging demand for chips,” “excessive power consumption by data centers,” or “high valuations.” However, people only have so much time to focus on these stories, and only a few will receive enough attention. These stories, amplified by numerous research reports, media coverage, and investor discussions, ultimately guide the flow of capital and affect asset prices. In other words, AI provides you with 100 possible explanations for an event, but you can only listen to one, and it is this one that will shape the market.
2. More Attention Leads to Wilder Price Movements (and Vice Versa)
Attention and prices are in a mutually reinforcing cycle: if a stock suddenly rises, more people start to pay attention to it, leading to increased buying and further price increases, which in turn attracts even more attention. AI accelerates this cycle by speeding up the dissemination of information and the generation of analysis reports, resulting in more dramatic price movements. Conversely, if a story is disproven (for example, if a company’s performance fails to meet expectations), prices can plummet quickly.
3. Stories Move Faster than Reality; Be Cautious of “Expectations Falling Short”
AI can quickly predict the future market potential of an industry (e.g., “AI models could generate trillions in revenue over the next decade”), but it takes time for companies to build factories, sell products, and generate profits. This means prices often reflect “future stories” before the company’s actual fundamentals catch up. If the company does indeed make money, prices may stabilize; if not, they will fall. For example, if an AI-related stock’s price soars based on such predictions but the company’s actual profits only double the following year, the price will drop.
4. Some Assets Receive More Attention, Others Are Ignored, Leading to Varying Pricing Speeds
AI ensures that information reaches everyone simultaneously, but attention is concentrated on a few hot topics. Industries like AI and renewable energy see their prices quickly reflect changes in performance announcements, while less popular sectors may see no price movement even if their performance improves, unless someone notices. In other words, while AI eliminates the time lag in information dissemination, the scarcity of attention creates a time lag in price reactions—hot assets are priced more quickly, while less popular ones are priced more slowly.
5. Scarcity is Always Changing, but Time Constraints Remain Constant
In the past, the scarcity was of information (e.g., only a few people knew a company’s performance). Later, the scarcity shifted to understanding that information, but now that both information and understanding have become more accessible, the most scarce resource is human attention. For investors, this means:
- Assets with good fundamentals but little attention represent opportunities (you can profit when attention finally turns to them).
- Highly monitored assets carry the risk of overblown expectations (for example, prices may reflect projected profits for five years, which may not be achievable).
- In the long run, asset values are still determined by fundamentals, but fluctuations in attention can create short-term opportunities or risks.
Conclusion
AI generates a vast amount of information and stories, but our time is limited. Those who can capture people’s attention and exploit the time differences in how attention is distributed will have the power to influence the market and make money.